To address the limitations of traditional statistical models in simulating the time-frequency characteristics of sea clutter, a sea clutter data generation method based on an enhanced generative adversarial network (GAN) is proposed in this paper. The complex sea clutter is decomposed into amplitude and time-frequency components, which are separately fed into a variational autoencoder-Wasserstein generative adversarial network (VAE-WGAN) for training. The outputs are then integrated to synthesize complex signals with both amplitude and phase characteristics. To enhance the model performance, a gradient penalty mechanism is introduced to constrain the Lipschitz continuity of the discriminator, effectively mitigating the mode collapse. A self-attention module is incorporated to strengthen the model’s ability to capture localized strong scattering features, such as sea spikes, significantly improving the spatiotemporal correlation of generated signals. Experiments cover sea states 2～5, with three datasets of dimensions[64,64], [128,128], and[256,256]constructed for each sea state. Twelve cross-validation trials demonstrate that the synthetic data exhibit high consistency with measured data in amplitude distribution, normalized spectrum, temporal correlation, and time-frequency characteristics. These results validate the model’s generalization capability across varying sea states and multiscale temporal scenarios.

This study addresses the detection requirements of space-based distributed radar system for high-speed maneuvering space targets. Aiming at the problems of echo range migration and Doppler crossing caused by platform spatial position difference and target high-speed maneuvering characteristics, a spatio-temporal two-dimensional coherent accumulation method for space-based distributed radar is proposed. Based on the spatio-temporal phase history of target echoes, the algorithm designs a spatio-temporal joint compensation function between and within distributed radar nodes and incorporates the node spatial synthesis compensation and intra-channel target motion compensation into a unified processing framework. Firstly, an equivalent compensation function model is established under the distributed one transmitter and multi-receiver configuration, emulating a monostatic transceiver mode. Through envelope range correction and spatial phase difference compensation, the echo time-domain process of distributed nodes is completely unified, so as to achieve spatial coherent accumulation. Secondly, the time domain two-dimensional walk correction of the target echo in the node is carried out to realize the time domain pulse coherent accumulation of the high-speed maneuvering target. To enhance the computational efficiency, on the basis of generalized Radon-Fourier transform (GRFT), the target coherent accumulation problem is transformed into parameter estimation problems such as target angle, velocity, and acceleration, thereby the accumulation detection of space-based distributed radar for space targets is realized. Finally, the effectiveness of the method is evaluated by simulation experiments. The simulation results show that the method can accurately estimate the target parameters, and the coherent accumulation gain is consistent with the theoretical analysis.

Currently, sea-surface small targets have become the focus and difficulty of marine radar detection. The existing detection methods are limited to the use of unilateral information such as radar echo amplitude or spectrum, making it difficult to effectively detect small targets. Thus, a sea-surface small target detection method using dual-channel joint graph features (DC-JGF) is proposed in this paper. Firstly, the time-domain phase sequence and the frequencydomain amplitude sequence are extracted from the radar complex echo sequence to generate the time-frequency domain dual channel. In each channel, graphs are generated separately to provide rich correlation information. Secondly, in the time domain channel, the largest and the second-largest eigenvalues of graph Laplacian matrix are fused as the first feature to evaluate the graph density. In the frequency domain channel, by extracting non-zero elements from the diagonal of the degree matrix, the entropy value is calculated as the second feature to measure the dispersion of the vertex distribution of the graph. Then, the two features are used as detection statistics to determine whether they fall within the decision region given by the convex hull algorithm with target guidance. The detection results are obtained. Finally, experimental results using measured data demonstrate that the proposed detector can achieve robust and efficient detection performance in complex detection environments.

Spaceborne distributed interferometic synthetic aperture radar (InSAR) system flying in formation winding, the relative attitude change of the two satellites leads to the dynamic change of baseline system error. The traditional baseline estimation method of calculating the mean value of baseline calibration results for a single calibration site cannot be effectively applied to uncalibrated arcs. A baseline estimation method is proposed in this paper to solve this problem. The baseline system error and the system error of the two satellites are analyzed, and the baseline calibration result is converted to the satellite system error. Then the baseline error of the uncalibrated arc is calculated by combining the orbit parameters and motion attitude of the satellite. The variations of the elevation difference, the relative attitude and the system error of the traditional baseline estimation method and the proposed baseline estimation method during the flight of the satellite are simulated, and the experimental results are verified by the measured data of the Chinese spaceborne distributed InSAR system. The experimental results show that the proposed baseline estimation method can improve the ground elevation measurement accuracy of the uncalibrated arc compared with the traditional baseline estimation method, and provide a new method for the application of baseline calibration results of spaceborne distributed InSAR system.

In recent years, millimeter-wave radars have become more and more widely used in the field of smart transportation due to their small size, light weight, fast processing speed and high detection accuracy. Millimeter-wave radars have different beam systems and their principles are different. For beamforming (BF) system millimeter-wave radars, this paper first introduces the principle of beamforming and scanning, and then designs a suitable microstrip array antenna. The radar hardware RF board is developed by cascading four chips. On this basis, the process of obtaining data for radar target detection is given. Combined with the target data and point cloud features under the BF radar, a target point cloud clustering method using the regional growth idea is proposed. Finally, the feasibility and effectiveness of this method are verified through field experiments. By comparing with the traditional DBSCAN algorithm, this method can effectively solve the problem that two targets are easily clustered into one target when the distance between two targets is close. At the same time, it can effectively reduce the processing time when the number of point clouds is large. This method provides strong support for the application of target detection, tracking and recognition of the BF radar platform, and has broad application prospects and practical value.

Mode 5 signal used in the identification friend or foe (IFF) system adopts technologies such as Walsh soft spread spectrum and MSK modulation to improve the information capacity and security, while making specific emitter identification (SEI) of the Mode 5 signal difficult. To address this issue, two SEI methods for Mode 5 signal are proposed by using the fixed characteristics of synchronous pulse: SEI method based on the instantaneous phase features of synchronous pulses and SEI method based on the cross-correlation features of synchronous pulses. The simulation results show that under the condition of signal-to-noise ratio of 12dB, the accuracy of the method based on the instantaneous phase feature is 90.4%, and the accuracy of the method based on the cross-correlation feature is 94.8%. The performance of both SEI methods proposed in this paper is better than the traditional ones.

Aiming at the challenges of low target signal-to-noise ratio (SNR), susceptibility to direct wave and multipath interference, and other target detection problems arising from the use of non-cooperative illumination sources, this paper studies the reconfigurable intelligent surface (RIS)-assisted passive radar system which can enhance the echo SNR and the corresponding target parameter estimation method. On the basis of analyzing and establishing the RIS assisted passive radar system and signal model, firstly, the RIS configuration within the passive radar framework is explored. The RIS reflection coefficient optimization problem is established to improve the signal-to-clutter-plus-noise ratio (SCNR) of the received signal and ensure the direct wave receiving power. The global optimal solution of the RIS reflection coefficient is deduced theoretically, and the problem of weak target detection is solved fundamentally. Then, the signal processing method for RIS-assisted passive radar is investigated, and a multi-parameter estimation method based on time-varying RIS and sparse reconstruction is proposed, which can estimate the target parameters such as time delay, velocity, and azimuth simultaneously. Experimental results demonstrate the effectiveness and superiority of the proposed method.

Passive bistatic radar (PBR) avoids electromagnetic interference to a great extent because of the layout mode of transmitting and receiving separately. However, it faces a lot of short-range ground clutter interference in its work, and it is difficult to detect the target when it is submerged in a lot of clutter, especially for PBR with pulse radar as its external radiation source, the clutter processing is more difficult. In this paper, a time-domain monopulse extensive cancellation algorithm-clutter map (ECA-CMAP) clutter suppression method is proposed for PBR with pulse radar as external radiation source, aiming at the problem that it faces a large number of short-range ground clutter to cover up the target in practical work. Firstly, based on the classical time domain clutter suppression method ECA (extensive cancellation algorithm), an improved scheme based on clutter time delay estimation is proposed, which can suppress short-range ground clutter and keep the target intact, and the signal-to-clutter ratio is increased by nearly 50dB, and the target detection probability is further improved by using Nitzberg clutter map algorithm. Simulation and result of measured data processing verify the effectiveness of the algorithm.

Airborne spotlight synthetic aperture radar (Spotlight SAR) is a high resolution imaging mode of SAR. The basic principle is to achieve decimeter-level high-resolution imaging by continuous observation of fixed areas. This high-resolution imaging has extremely important applications in military and civilian fields, especially in target interpretation and recognition. However, with the improvement of resolution, in the long-term observation process, the moving target in the observation area will produce longer and more complex defocus and offset signals. When these signals cover important objects such as urban buildings, the effect of image interpretation and target recognition will be significantly reduced. In view of the above problems, two methods of moving target interference suppression are proposed in this paper. The first method is to combine the relative velocity with the range Doppler algorithm (RDA), and adjust the relative velocity parameters iteratively so that the defocused moving target can be refocused. In each iteration, the refocusing effect of the moving target is tested and judged by the maximum amplitude index. After the refocusing is completed, the refocused moving target is separated by the mask, and the original moving target echo signal is recovered by the inverse echo operation. Finally, by subtracting the recovered moving target echo from the original echo signal, the echo signal of the static scene can be obtained, and then the range Doppler algorithm is used to realize the imaging of the static scene. The second method is a moving target interference suppression method based on image sequence. The method obtains an image sequence by segmenting the sub-aperture, detects and generates a mask in the sub-aperture image sequence to remove the defocusing moving target signal, and then accumulates the processed image sequence complex data to generate a high-resolution static scene image. In this paper, semi-physical synthetic data are used for experiments, and evaluated by correlation and coherence operations. The experimental results show that the first method can effectively separate the moving target from the static scene echo and the effect is better than the second method.

The traditional satellite size estimation method based on RCS data mainly uses ellipsoid model for equivalence, which is not accurate enough for estimating the size of rectangular satellites. This article mainly studies the size estimation technology of rectangular satellite. Based on the RCS equivalent formula of the rectangular flat plate that constitutes the rectangular satellite, the relationship between the length and width of the rectangular flat plate and the RCS sequence characteristics is studied; By modeling the motion attitude of a rectangular satellite, the calculation of the satellite’s in orbit motion attitude angle has been achieved. Based on the above research, a method for estimating the size of rectangular satellite based on RCS data is proposed, which can estimate the length and width of rectangular satellite by using RCS data. The experimental results show that this method can effectively improve the accuracy of size estimation for rectangular satellites, providing a new method and idea for spatial target feature recognition.